Top Gen AI trends to impact insurers and MGAs in 2025

NEW YORK, December 10, 2024 — Generative AI has led to constructive disruption in the insurance industry, helping streamline operations, enabling more tailored and profitable product offerings, improving fraud detection, and supporting faster, more informed policyholder services in policy and claims management. However, current use cases and benefits are just the start, according to NeuralMetrics, a leading provider of generative AI technology and data for commercial risk assessment, which anticipates generative AI deployment among insurers and MGAs to increase substantially in 2025.

The company highlights five AI trends expected to drive modernization in the insurance industry next year:

• Agentic AI raises the bar for operational proficiency and results. The first wave of AI was rule-based, the second wave was focused on machine learning, and the emerging third wave is agentic. Expect insurance organizations to move beyond machine learning to implement cognitive, role-based AI agents or assistants across all areas of the insurance workflow. AI assistants can assume distinct personas, such as a risk appetite or a claims experience expert coworkers in support of functional teams. Autonomous AI assistants are poised to take generative AI to the next level of operational productivity. They can learn quickly, be trained and retrained easily, locate and access fresh data in real time, and adapt to new information and processes efficiently.
• The perfect feedback loop will be an AI ecosystem: Insurance organizations will begin to adopt multiple cognitive and adaptive AI assistants to take on several types of knowledge work and basic tasks. Additionally, AI assistants will transition from operating in silos and become adept in communicating across functional areas and processes — creating a feedback loop and supporting the virtuous circle of insurance operations, for example, by coordinating workflows in the areas of risk appetite and analysis, policy quoting/pricing and claims experience to ensure underwriting guidelines are optimized.
• AI assistants will communicate like people. We’re already seeing plain language capabilities in AI solutions like ChatGPT.  Those qualities will proliferate among the autonomous AI coworkers that insurance organizations deploy. Users can interact and manage AI assistants more naturally and intuitively — as the technology improves and more directly supports various teams in critical operational areas of the insurance lifecycle.
• Grounding AI sets the table for building trust. Accuracy of risk-quality information and transparency of data sourcing by AI is a priority for every insurance organization, particularly as new state and federal regulations continue to evolve. Expect more focus on grounding AI, which can connect AI output to verifiable sources of information. By providing models with access to specific data sources, grounding can tether AI-generated information and actions to source data, thereby reducing “hallucinations” and helping build trust in emerging AI technology's implications and output.
• The great people replacement fear is overstated, and business-enabling AI will prompt interest and acceptance. As insurance organizations experiment with generative AI, there will be a growing realization that the technology isn’t outthinking them — it’s making their work more refined and effective. The apprehensions of people being replaced by AI will continue to dissipate. Instead, the focus will shift to optimizing AI within insurance operations and workflows across the industry's value chain.

"The role and impact of AI in insurance business operations is expanding rapidly, so insurers and MGAs must prepare for the coming layers of innovation and cost-efficiency,” said Prakash Vasant, CEO of NeuralMetrics. “In working with our insurer clients, we’re participating in some of the most critical trends that expand generative AI use from improving basic and redundant workflows to a strategic solution that can assist in modernizing and transforming the business of insurance, for example by adding capacity, on-demand risk insights, and cost-efficiency, in commercial underwriting.